The Stata package “multilevel tools” (mlt) includes a range of ado-files for postestimation after multilevel models (xtmixed/xtmelogit). Up to now, it contains three commands (more ado-files will be added in the future): mltrsq gives the Boskers/Snijders R-square and the Bryk/Raudenbusch R-square values. mltcooksd gives the influence measures Cook’s D and DFBETAs for the higher-level units in hierarchical mixed models. mltshowm presents how the model looks if those cases detected as influential are excluded from the sample. In our presentation, we will discuss the issue of influential cases in multilevel modeling. We will use some research examples to stress the importance of considering influential cases, particularly in multilevel analysis. We will show how the influence measures for second-level units are defined and how we calculate them.
